The present invention relates to a method for optimising formulations against a number of criteria. The method can advantageously be applied by using a computer operated optimisation process.
1. Field of the Invention
An example of a optimisation method of this type is known in practice as CAD/Chem. The method comprises the use of a neural net model which provides property predictions on the input of a candidate formulation. An optimisation algorithm is used to find a formulation against a set of desired properties. Property weights must be assigned to each property to indicate the relative importance of each particular property. Constraints on formulation ingredients and processing parameters may be expressed as rules. This method forces the user to assign a relative ranking to the criteria against which the formulation is to be optimised before running the optimisation algorithm, so that although an optimised formulation is obtained the relative ranking is an inherent part of this formulation found, wherein the user can not see the effect of trade-offs between the criteria.
WO 9720076 discloses methods for optimising multicomponent formulations, wherein a large number of mixtures are analysed to determine the formulation(s) with optimal properties. In this known method a marker is associated with each candidate formulation. It will be clear that this method is time consuming and requires significant amounts of labour and costs.
U.S. Pat. No. 5,940,816 discloses a method for using a computer for multi-objective decision-support to improve a candidate solution for a transportation problem. There is no suggestion that this method is suitable to support in optimising formulations.
2. The Related Art
The invention aims to provide an improved method for using a computer for optimising formulations against a number of criteria.
According to the invention a method is provided for optimising formulations against a number of criteria, comprising the steps of
(a) providing a model algorithm for each of the criteria, each model algorithm providing a prediction for a corresponding criteria when a candidate formulation is inputted into the model algorithm; and
(b) selecting criteria to optimise a set of candidate formulations; and
(c) providing an algorithm for optimisation of the set of candidate formulations in accordance with the selected criteria;
wherein a first set of one or more candidate formulations is provided and wherein the optimisation algorithm generates one or more new candidate formulations and wherein all candidate formulations are inputted into the number of model algorithms to obtain predictions, and wherein information of the set to candidate formulations obtained by said generation and/or previous optimisations and/or experiments is used to select candidate formulations from the set to obtain a Pareto optimal set of candidate formulations.
In this manner a method is provided by means of which a Pareto optimal set of candidate formulations is obtained with varying trade-offs between criteria. The trade-offs between different desired criteria can be examined in an easy manner without the effort of preparing large numbers of mixtures. The information obtained can be used in further selecting formulations for further actual testing of formulations.
For the purpose of the invention the term formulation optimisation refers to the fact that for a formulation the type of ingredients, their relative levels and the conditions of preparing the final formulation are chosen such that an desired end formulation is obtained.
For example an optimisation with reference to the type of ingredient may provide assistance is determining which choice out of a number of alternatives can be used. For example choice of emulsifiers, surfactants, thickeners etc.
An optimisation with reference to the relative level of ingredients may for example start from a list of ingredients and aim to find an optimised combination of those. For example the optimisation process may provide an indication of ratios of surfactant materials or fat mixtures in products.
An optimisation with reference to the conditions for preparing the final formulation may for example take into account processing conditions such as temperature, mixing speed, maturing times and aim to find optimal combinations of these.
Very often a formulation optimisation process in accordance to the invention will take into account more than one of the above elements. Preferred optimisation processes in according to the invention involve the optimisation with reference to the relative level of ingredients as described above. This may then optionally be combined with optimisation with respect to the type of ingredients and/or with reference to the manufacturing conditions.
According to a preferred embodiment the method of the invention can include a number of iteration steps in a loop as follows:
(i) a first set of one or more candidate formulations are used as starting point;
(ii) candidate formulations are inputted into the number of model algorithms to obtain predictions, and
(iii) the optimisation algorithm generates one or more new candidate formulations; and
(iv) the new candidate formulations are used as input into the number of model algorithms in iteration step (ii),
and wherein a Pareto optimal set of predictions are determined for selecting the candidate formulations.